Research, design, and deploy ML/AI models and systems into production.
Translate business needs into data-driven solutions in collaboration with product, engineering, and other stakeholders.
End-to-end ownership: from experimentation and prototyping to production deployment and monitoring.
Contribute to team best practices and mentor junior colleagues.
Build AI-powered solutions (LLMs, generative models) that move ideas from research and experimentation to robust production systems that power Pendo’s product experiences.
Solve real customer problems and deliver functional, applicable, transformative AI features.
Requirements
B.Sc. in Computer Science, Statistics, Data Science, or related field.
5+ years of professional experience applying ML/AI in production systems.
Hands-on experience delivering LLM-powered features to production (e.g., RAG pipelines, prompt orchestration, evaluation/guardrails, monitoring).
Experience in cloud platforms (AWS, GCP, or Azure), distributed systems, and MLOps best practices.
Solid knowledge of statistical modeling, experimental design, and applied ML/AI methods.
Proficiency in Python and core ML/AI libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
Proven experience in deploying and maintaining production ML/AI systems.
(Preferred) Advanced degree (MSc or PhD) in Computer Science, Statistics, Data Science, or related field.
(Preferred) Track record of research contributions (patents, or open-source contributions).
(Preferred) Deep cross-functional collaboration with Product and Engineering; able to explain complex concepts to diverse technical audiences, align team members, and drive delivery.
ATS Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
B.Sc. in Computer ScienceB.Sc. in StatisticsB.Sc. in Data ScienceMSc in Computer ScienceMSc in StatisticsMSc in Data SciencePhD in Computer SciencePhD in StatisticsPhD in Data Science